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Adds export functionality to chat, removes poetry in favor of uv, bumps Honcho version to v0.0.14/python-SDK-0.0.19 #15

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Adds export functionality to chat, removes poetry in favor of uv, bumps Honcho version to v0.0.14/python-SDK-0.0.19 #15

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b908a3b
Adds `export` functionality to chat, removes poetry in favor of uv.
bLopata Jan 7, 2025
f990741
Bump honcho version.
bLopata Jan 7, 2025
1104be1
Bump honcho version in toml file.
bLopata Jan 7, 2025
b678112
Update webshell/Dockerfile
bLopata Jan 8, 2025
9756163
Adds backwards compatability for existing share links with UUIDS, cha…
bLopata Jan 14, 2025
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36 changes: 14 additions & 22 deletions Dockerfile
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Original file line number Diff line number Diff line change
Expand Up @@ -2,30 +2,24 @@
# https://testdriven.io/blog/docker-best-practices/
FROM python:3.11-slim-bullseye

RUN apt-get update && apt-get install -y build-essential
RUN apt-get update && apt-get install -y build-essential curl

WORKDIR /app

# https://stackoverflow.com/questions/53835198/integrating-python-poetry-with-docker
# Set Python environment variables and default port
ENV PYTHONFAULTHANDLER=1 \
PYTHONUNBUFFERED=1 \
PYTHONHASHSEED=random \
PIP_NO_CACHE_DIR=off \
PIP_DISABLE_PIP_VERSION_CHECK=on \
PIP_DEFAULT_TIMEOUT=100 \
POETRY_VERSION=1.8.3
PYTHONUNBUFFERED=1 \
PYTHONHASHSEED=random \
PORT=8000

RUN pip install "poetry==$POETRY_VERSION"
# Install uv and add to PATH
RUN curl -LsSf https://astral.sh/uv/install.sh | sh && \
mv /root/.local/bin/uv /usr/local/bin/ && \
mv /root/.local/bin/uvx /usr/local/bin/

# Copy only requirements to cache them in docker layer
WORKDIR /app
COPY poetry.lock pyproject.toml /app/

# Project initialization:
RUN poetry config virtualenvs.create false \
&& poetry install --no-root --no-interaction --no-ansi

WORKDIR /app
# Copy requirements and install dependencies
COPY requirements.txt .
RUN uv pip install --system -r requirements.txt
Comment on lines +20 to +22
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Should probably be a uv sync command. Should follow conventions from honcho repo or on https://docs.astral.sh/uv/guides/integration/docker/


RUN addgroup --system app && adduser --system --group app
RUN chown -R app:app /app
Expand All @@ -34,7 +28,5 @@ USER app
COPY --chown=app:app app.py /app/app.py
COPY --chown=app:app calls.py /app/calls.py

EXPOSE 8000

# https://stackoverflow.com/questions/29663459/python-app-does-not-print-anything-when-running-detached-in-docker
CMD ["fastapi", "run", "app.py", "--host", "0.0.0.0", "--port", "8000"]
EXPOSE ${PORT}
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internal port doesn't matter we can always change what port we expose on the outside. should just keep this to static port

CMD uvicorn app:app --host 0.0.0.0 --port ${PORT}
86 changes: 77 additions & 9 deletions app.py
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@@ -1,26 +1,30 @@
import os
from contextvars import ContextVar
from typing import Annotated, Any, Dict
from typing import Annotated, Any, Dict, List, Literal
from functools import cache
from fastapi.security import OAuth2PasswordBearer
from fastapi.responses import HTMLResponse, FileResponse
from fastapi.staticfiles import StaticFiles

import sentry_sdk
from fastapi import Depends, FastAPI, HTTPException, status
from starlette.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse
from fastapi.responses import StreamingResponse, FileResponse
from honcho import Honcho
from pydantic import BaseModel

from cryptography.fernet import Fernet
import base64

from calls import GaslitClaude, Simulator

import jwt


from dotenv import load_dotenv

import tempfile
import json
from datetime import datetime

load_dotenv(override=True)


Expand All @@ -35,13 +39,23 @@ def get_env(key: str):
CLIENT_REGEX = get_env("CLIENT_REGEX")
print(CLIENT_REGEX)
JWT_SECRET = get_env("JWT_SECRET")
SECRET_KEY = base64.b64decode(get_env("SECRET_KEY"))
SECRET_KEY = get_env("SECRET_KEY").encode()
HONCHO_APP_NAME = get_env("HONCHO_APP_NAME")

fernet = Fernet(SECRET_KEY)

honcho = Honcho(base_url=HONCHO_ENV)
honcho_app = honcho.apps.get_or_create(HONCHO_APP_NAME)
print(f"Initializing Honcho with base_url: {HONCHO_ENV}")
honcho = Honcho(
base_url=HONCHO_ENV,
)

try:
print(f"Attempting to get/create app: {HONCHO_APP_NAME}")
honcho_app = honcho.apps.get_or_create(HONCHO_APP_NAME)
print(f"Successfully initialized app with id: {honcho_app.id}")
except Exception as e:
print(f"Error initializing Honcho app: {str(e)}")
raise


gaslit_ctx = ContextVar(
Expand Down Expand Up @@ -72,7 +86,6 @@ def get_env(key: str):
allow_headers=["*"],
)


class BaseRequest(BaseModel):
session_id: str

Expand Down Expand Up @@ -212,10 +225,24 @@ async def reset(
honcho.apps.users.sessions.delete(
app_id=honcho_app.id, session_id=session_id, user_id=user_id
)
session = honcho.apps.users.sessions.create(app_id=honcho_app.id, user_id=user_id)
# TODO reset the session
# gaslit_claude.history = []
# simulator.history = []
try:
session = honcho.apps.users.sessions.create(
app_id=honcho_app.id,
user_id=user_id,
)
except TypeError as e:
if "location_id" in str(e):
# If location_id is truly optional, try without it
session = honcho.apps.users.sessions.create(
app_id=honcho_app.id,
user_id=user_id
)
else:
raise e

Comment on lines +269 to +283
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Is this for backwards compatability?

return {
"user_id": user_id,
"session_id": session.id,
Expand Down Expand Up @@ -299,3 +326,44 @@ async def share_messages(code: str):
return await get_session_messages(session_id=session_id, user_id=user_id)
except Exception:
raise HTTPException(status_code=400, detail="Invalid encrypted data")

class MessageFormat(BaseModel):
role: Literal["user", "assistant"]
content: str

@app.get("/export/{session_id}")
async def export_session(session_id: str, user_id: str = Depends(get_current_user)):
try:
messages = honcho.apps.users.sessions.messages.list(
app_id=honcho_app.id,
user_id=user_id,
session_id=session_id
)

formatted_messages = [
{
"role": "user" if msg.is_user else "assistant",
"content": msg.content
} for msg in messages
]

# Create a temporary file
with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.json') as tmp:
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is writing to disk necessary here? i feel like this could be done in memeory

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or is this already in memory? i've never used this library before, if so, neat trick.

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@bLopata bLopata Jan 8, 2025 •
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From python docs
tempfile.TemporaryFile(mode='w+b', buffering=-1, encoding=None, newline=None, suffix=None, prefix=None, dir=None, *, errors=None) Return a [file-like object](https://docs.python.org/3/glossary.html#term-file-like-object) that can be used as a temporary storage area. The file is created securely, using the same rules as [mkstemp()](https://docs.python.org/3/library/tempfile.html#tempfile.mkstemp). It will be destroyed as soon as it is closed (including an implicit close when the object is garbage collected). Under Unix, the directory entry for the file is either not created at all or is removed immediately after the file is created. Other platforms do not support this; your code should not rely on a temporary file created using this function having or not having a visible name in the file system.

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Output from claude about it. Maybe we should used SpooledTemporaryFile

The Python tempfile library provides both in-memory and on-disk temporary storage options. Let me explain the key functionality:

For on-disk temporary files and directories:

  • tempfile.NamedTemporaryFile(): Creates a temporary file on disk with an actual file name in the filesystem. By default, it's automatically deleted when closed.
  • tempfile.mkstemp(): Creates a temporary file on disk and returns both a file descriptor and the file path. Doesn't automatically delete the file.
  • tempfile.mkdtemp(): Creates a temporary directory on disk and returns its path.

For in-memory temporary storage:

  • tempfile.SpooledTemporaryFile(): Creates a file-like object that initially stores data in memory. If the data exceeds a size threshold (default 0.5MB), it automatically switches to using disk storage.

Here's a practical example:

import tempfile

# On-disk temporary file
with tempfile.NamedTemporaryFile() as tf:
    tf.write(b"Some data")
    tf.seek(0)
    print(tf.read())  # File is automatically deleted after this block

# In-memory with potential disk spillover
with tempfile.SpooledTemporaryFile(max_size=1024) as tf:
    tf.write(b"In memory until exceeding 1KB")
    tf.seek(0)
    print(tf.read())

The temporary files are created in your system's default temporary directory (usually /tmp on Unix-like systems or the user's temp directory on Windows). This location can be customized using the dir parameter in these functions.

Would you like me to explain any specific aspect in more detail?

json.dump(formatted_messages, tmp, indent=2)
tmp_path = tmp.name

timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"yousim_conversation_{timestamp}.json"

return FileResponse(
path=tmp_path,
filename=filename,
media_type='application/json',
background=None # Ensures file is sent before deletion
)

except Exception as e:
raise HTTPException(
status_code=400,
detail=f"Failed to export session: {str(e)}"
)
9 changes: 7 additions & 2 deletions docker-compose.yml
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@@ -1,12 +1,15 @@
version: '3.8'
# version: '3.8'

services:
backend:
build:
context: .
dockerfile: Dockerfile
ports:
- "8000:8000"
- "${PORT}:${PORT}"
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why do we care about the port within the container?

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I made this more complicated than needed because I was running my honcho fastAPI on (the default) port 8000, so I was specifying here to avoid any problems. I will fix this.

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Should just stick to default setup in the compose. Can change as we need in local development, but shouldn't push it up.

environment:
- HONCHO_AUTH_TOKEN=default
- PORT=${PORT}
env_file:
- .env

Expand All @@ -18,3 +21,5 @@ services:
- "3000:3000"
depends_on:
- backend
env_file:
- ./webshell/.env
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